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Hamilton Airshed Modelling System

  • Anthony Ciccone
  • Janya KellyEmail author
  • James Wilkinson
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

The objective of this study is to develop the Hamilton Airshed Modelling System (HAMS) providing a platform to better understand the processes and contributions to Hamilton’s air quality, informing future policy and human health impact decisions. Air quality in an urban airshed is influenced by local, regional and transboundary sources, geography and meteorology. HAMS must handle different emission sources, and the transportation and dispersion of emissions, to achieve realistic simulations of local impacts on air quality. HAMS relies on the development of two key data sets. The meteorology dataset impacts the transportation, transformation, dispersion, and deposition of pollutants over the challenging terrain in the Hamilton area. The emissions dataset represents the local and regional sources and contaminants influencing the air quality with contributions from industrial, commercial, residential, biogenic, and transportation sources. The Community Multi-scale Air Quality (CMAQ) model combines these datasets in a nested a one-way grid formation from regional (36 km) to local (1.33 km) scales and validates modeled output against observations. Recent local studies indicate that mobile and industrial sources are the primary emission sources. This study further examines the source contributions of mobile, industrial and background sources to local impacts on air quality.

Keywords

Air quality model Hamilton CMAQ Source contribution 

Notes

Acknowledgements

Golder would gratefully like to acknowledge the following contributions which made the Hamilton Airshed Modelling System possible. The initial and boundary conditions from GEOS-CHEM were provided by Dr. Barron Henderson and his research team at the University in Florida. Environment and Climate Change Canada provided the SMOKE ready national emissions inventory for Canada, as well as Paul Makar and Junhua Zhang providing technical expertise on processing emissions in SMOKE and interpreting the impact on modelled concentrations. Finally, Golder would like to thank the Project Steering Committee and the Hamilton Industrial Environmental Association for providing continued direction during the project.

References

  1. 5.
    CMAS, Operational Guidance for the Community Multiscale Air Quality (CMAQ) Modeling System (2015). Retrieved from https://www.airqualitymodeling.org/index.php/CMAQ_version_5.0_(February_2010_release)_OGD
  2. 2.
    CMAS, Community Modeling & Analysis System. SMOKE v.3.6 (2014). Retrieved from https://www.cmascenter.org/smoke/
  3. 1.
    NCAR, Weather Research and Forecasting Model (2018). Retrieved from https://www.mmm.ucar.edu/weather-research-and-forecasting-model
  4. 3.
    UCAR, Model of Emissions of Gases and Aerosols from Nature (MEGAN) (2015). Retrieved from http://lar.wsu.edu/megan/index.html
  5. 4.
    USEPA, Motor Vehicle Emission Simulator (2014). Retrieved from http://www.epa.gov/otaq/models/moves/

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Golder Associates LtdMississaugaCanada
  2. 2.Terra-TechnologiesEugeneUSA

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